Data Engineering Podcast

AUGUST 21, 2022

Ascend users love its declarative pipelines, powerful SDK, elegant UI, and extensible plug-in architecture, as well as its support for Python, SQL, Scala, and Java. Can you describe what is driving the adoption of real-time analytics?

Lambda Architecture 100

Lambda Architecture MongoDB MySQL Scala 100

Data Engineering Podcast

MAY 29, 2022

By supporting fast, in-memory row-based queries and columnar on-disk representation, it lets your transactional and analytical workloads run in the same database. Ascend users love its declarative pipelines, powerful SDK, elegant UI, and extensible plug-in architecture, as well as its support for Python, SQL, Scala, and Java.

Database 100

Database Architecture Data Architecture PostgreSQL 100

Towards Data Science

JANUARY 16, 2024

In my then limited experience as a Data Engineer, I had only come across centralised data architectures and they seemed to be working very well. So, I was left wondering what was it that we wanted to solve using a decentralised data architecture? Or were we creating a new problem that did not ever exist in the first place?

Data Warehouse 95

Data Warehouse Data Architecture Relational Database NoSQL 95

DataKitchen

AUGUST 19, 2021

Figure 3: Example DataOps architecture based on the DataKitchen Platform. Figure 3 shows an example processing architecture with data flowing in from internal and external sources. The data scientists and analysts have what they need to build analytics for the user. The new Recipes run, and BOOM! Pharma Data Mesh Domains.

Pharmaceutical 98

Pharmaceutical Data Lake Data Warehouse Raw Data 98

ThoughtSpot

JUNE 24, 2024

To ensure you’re not swept away in the changing tides, you need a modern solution founded with the vision and expertise required to deliver search-based analytics. This entire experience can only come together the way it has with the right analytics architecture, semantic engine, and consumer UX.

BI 59

BI Analytics Architecture SQL Cloud 59

Monte Carlo

FEBRUARY 9, 2022

Insights is] a new and powerful way to understand what data assets matter most to our business and how we can better drive an impact with our data across the organization,” s aid Valerie Rogoff , Director of Data Analytics Architecture at ShopRunner.

Raw Data 52

Raw Data Analytics Architecture Data Data Analytics 52

Data Engineering Weekly

NOVEMBER 13, 2022

Data Engineering Weekly Is Brought to You by RudderStack RudderStack provides data pipelines that make it easy to collect data from every application, website, and SaaS platform, then activate it in your warehouse and business tools. Sign up free to test out the tool today. The schematization of data plays a vital role in a data platform.

Data Engineer 52

Data Engineer Data Engineering Engineering Kafka 52

Striim

AUGUST 22, 2024

Moreover, there are two forms of real-time analytics. These include: On-demand real-time analytics With on-demand real-time analytics, users send a request, such as with an SQL query, to deliver the analytics outcome. It delivers analytics continuously in real time without requiring a user to make a request.

Data Warehouse 52

Data Warehouse Retail Machine Learning Database 52

Rockset

JULY 8, 2021

We spend a lot of time thinking about running analytics on MongoDB, as do many MongoDB users we speak with. Real Time Analytics with MongoDB Change Streams MongoDB Change Streams, essentially MongoDB's version of change data capture (CDC), is a very useful tool for getting MongoDB data into an analytics-optimized store in real time.

MongoDB 40

MongoDB Manufacturing Analytics Architecture Architecture 40

Monte Carlo

JULY 25, 2022

But one thing’s for sure: if you can’t trust the data powering your analytics architecture, it’s hard to justify the investment. Federated governance Even while democratizing access to and ownership of data, the data mesh architecture includes a thorough approach to governance.

Government 52

Government Data Architecture Insurance 52

Rockset

MARCH 19, 2020

In this post, I’ll discuss some common real-time analytics use-cases that we have seen with our customers here at Rockset and how different real-time analytics architectures suit each of them. First, an obligatory aside on real-time analytics. This type of setup is kind of the “hello world” of Kafka streaming analytics.

Kafka 40

Kafka Database Process SQL 40

Knowledge Hut

FEBRUARY 27, 2023

Data engineering is all about building, designing, and optimizing systems for acquiring, storing, accessing, and analyzing data at scale. Data engineering builds data pipelines for core professionals like data scientists, consumers, and data-centric applications. The average salary for a Machine Learning Engineer is S$7448 per month in Singapore.

Data Engineer 52

Data Engineer Data Engineering Database-centric Pipeline-centric 52

Edureka

FEBRUARY 7, 2023

It is possible to use Azure SQL Database, Azure SQL Managed Instance and Azure Synapse Analytics. It allows developers to query external data from supported data stores transparently, regardless of the storage architecture of the external data store. 7) Describe the Azure Synapse Analytics architecture.

Data Engineer 52

Data Engineer Data Engineering Engineering Hadoop 52

Towards Data Science

MAY 22, 2023

Solving data preparation tasks with ChatGPT Photo by Ricardo Gomez Angel on Unsplash Data engineering makes up a large part of the data science process. In CRISP-DM this process stage is called “data preparation”. It comprises tasks such as data ingestion, data transformation and data quality assurance. So why not try to automate it with an LLM?

Data Engineer 98

Data Engineer Data Engineering Engineering Data Science 98

Monte Carlo

MAY 17, 2023

Data observability, an organization’s ability to fully understand the health and quality of the data in their systems, has become one of the hottest technologies in modern data engineering. In less than three years it has gone from an idea sketched out in a Barr Moses blog post to climbing the Gartner Hype Cycle for Emerging Technology.

Data 52

Data Data Pipeline Data Engineering Data Engineer 52

Monte Carlo

MAY 17, 2023

Data observability, an organization’s ability to fully understand the health and quality of the data in their systems, has become one of the hottest technologies in modern data engineering. In less than three years it has gone from an idea sketched out in a Barr Moses blog post to climbing the Gartner Hype Cycle for Emerging Technology.

Data Pipeline 52

Data Pipeline Data Engineering Data Engineer Data 52